Commit d934c519 authored by Anne  BITON's avatar Anne BITON
Browse files

eval=TRUE for MCA correlation and save RDS instead of RDA

parent da666fae
......@@ -304,7 +304,7 @@ Warning: the cell annotation is assigned to the most correlated cell type, as av
We assign 'NA' to the cell types assigned by scMCA that match less than 10 cells (to make the plot a bit more readable).
```{r mca by condition and then across conditions, fig.width=12, fig.height=10, eval=FALSE}
```{r mca by condition and then across conditions, fig.width=12, fig.height=10, eval=TRUE}
mca_result <- scMCA::scMCA(scdata = sceall_seurat@assays$RNA@data, numbers_plot = 3)
# assignments to top correlations are in
#mca_result$scMCA
......@@ -320,13 +320,13 @@ sceall_seurat$scMCA_score <- apply(mca_result$cors_matrix, 2, max)
```
```{r mca plot by condition and then across conditions, fig.width=10, fig.height=5, eval=FALSE}
```{r mca plot by condition and then across conditions, fig.width=10, fig.height=5, eval=TRUE}
DimPlot(object = sceall_seurat , reduction = "umap", group.by = "scMCA", cells = colnames(sceall_seurat)[which(sceall_seurat$scMCA != 'NA')], pt.size = 1, dims = c(1,2))
```
```{r mca score by condition and then across conditions, fig.width=8, fig.height=6, eval=FALSE}
```{r mca score by condition and then across conditions, fig.width=8, fig.height=6, eval=TRUE}
FeaturePlot(object = sceall_seurat , reduction = "umap", features = "scMCA_score", pt.size = 1, dims = c(1,2))
......@@ -335,11 +335,11 @@ FeaturePlot(object = sceall_seurat , reduction = "umap", features = "scMCA_score
```{r, cache.rebuild=TRUE}
```{r}
saveRDS(sceall_seurat, file = paste0(dirdata,'derived/FL/sceall_seurat_fastMNN_bycond.rds'))
saveRDS(sceall_seurat, file = paste0(dirdata,'derived/FL/FL_sceall_seurat_fastMNN_bycond.rds'))
saveRDS(sceall_seurat, file = paste0(dirdata,'derived/FL/sceall_seurat_fastMNN_bycond_precluster.rds'))
saveRDS(sceall_seurat, file = paste0(dirdata,'derived/FL/FL_sceall_seurat_fastMNN_bycond_precluster.rds'))
```
......
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